| {"version": "v2.0", "data": [{"title": "Rainfall", "paragraphs": [{"qas": [{"is_impossible": false, "question": "How good is the estimate of peak precipitation?", "id": "145", "answers": [{"text": "peak precipitation is still significantly underestimated", "answer_start": 257}]}, {"is_impossible": false, "question": "Where is the dry bias?", "id": "146", "answers": [{"text": "central US region", "answer_start": 200}]}, {"is_impossible": false, "question": "When irrigation is turned on, what happens to nighttime precipitation", "id": "147", "answers": [{"text": "total precipitation increases by 20-30% during the strongly precipitating nighttime", "answer_start": 31}]}, {"is_impossible": true, "question": "What grid spacing do you need to resolve isolated convection?", "id": "148", "answers": []}, {"is_impossible": true, "question": "How well does the model resolve the LLJ?", "id": "149", "answers": [], "plausible_answers": [{"text": "does not fully resolve", "answer_start": 706}]}], "context": "With irrigation turned on, the total precipitation increases by 20-30% during the strongly precipitating nighttime and by 50-80% during the less precipitating daytime, and the overall dry bias in the central US region is reduced by 30-50%. The magnitude of peak precipitation is still significantly underestimated, which suggests irrigation effects can only partially account for the precipitation deficit over the central United States. Other biases in the model, such as LLJ and associated moisture transport, coupled with land-atmosphere interactions, and various feedback processes, uncertainties associated with 4km grid spacing properly representing shallow convection and convective triggering (4km does not fully resolve isolated convection), and PBL processes may also contribute to the bias."}]}, {"title": "Landslides ", "paragraphs": [{"qas": [{"is_impossible": false, "question": "What is the most prevalent hazards in the Himalaya?", "id": "150", "answers": [{"text": "Landslides", "answer_start": 0}]}, {"is_impossible": false, "question": "What causes accelerated erosion in the Himalayas?", "id": "151", "answers": [{"text": "Deforestation and construction", "answer_start": 351}]}, {"is_impossible": false, "question": "When do land slides become devastating?", "id": "152", "answers": [{"text": "When it occurs adjacent to human settlements and infrastructures, such as towns, roads, bridges and utilities.", "answer_start": 101}]}, {"is_impossible": true, "question": "How can geomorphic and tectonic data help mitigate future disasters?", "id": "153", "answers": []}, {"is_impossible": true, "question": "What data needs to be exchanged to ensure that the proper procedures and policies are put into effect in a timely fashion?", "id": "154", "answers": [], "plausible_answers": [{"text": "geomorphic and tectonic data", "answer_start": 517}]}], "context": "Landslides are one of the most prevalent hazards in the Himalaya and can be particularly devastating when it occurs adjacent to human settlements and infrastructures, such as towns, roads, bridges and utilities. Land sliding is common in the Himalaya because of the active seismicity, great relief, heavy monsoon rains, and accelerated erosion due to deforestation and construction. In the wake of this recent disaster, it is ever more apparent that new standards in home and road construction, and planning based on geomorphic and tectonic data are needed to help mitigate future disasters. For effective landslide hazard reduction the analysis of slope failures requires a comprehensive analysis of the landscape using modern technologies and data exchange to ensure that the proper procedures and policies are put into effect in a timely fashion (Saha and Gupta, 2002)."}]}, {"title": "atmospheric optical turbulence", "paragraphs": [{"qas": [{"is_impossible": false, "question": "What is the main mechanism accounting for clear air reflections in the UHF range?", "id": "155", "answers": [{"text": "Bragg scattering from spatial irregularities of refractive index created by turbulent mixing in regions in which there is a spatial gradient (usually vertical) of the refractive index", "answer_start": 291}]}, {"is_impossible": false, "question": "What spatial scale is the radar sensitive to?", "id": "156", "answers": [{"text": "half the radar wavelength", "answer_start": 583}]}, {"is_impossible": false, "question": "What does the C_n^2 structure parameter do?", "id": "157", "answers": [{"text": "characterizes the strength of the refractive index fluctuations", "answer_start": 914}]}, {"is_impossible": true, "question": "What is isentropic turbulence?", "id": "158", "answers": []}, {"is_impossible": true, "question": "What is the range of scales that mixing produces irregularities over?", "id": "159", "answers": [], "plausible_answers": [{"text": "half the radar wavelength", "answer_start": 583}]}], "context": "The radar reflectivity \ud835\udf02 of the atmosphere (units m^2 m^-3) may be written as the sum of the reflectivity \ud835\udf02_a of the clear air and the reflectivity \ud835\udf02_d of the drops that constitute rain and cloud. In the UHF range (300 to 3000 MHz) the main mechanism accounting for clear air reflections is Bragg scattering from spatial irregularities of refractive index created by turbulent mixing in regions in which there is a spatial gradient (usually vertical) of the refractive index. Mixing produces irregularities over a wide range of scales. The radar is sensitive to the spatial scale of half the radar wavelength. Clear air provides a detectable target if the irregularities of this scale are sufficiently strong. For isotropic turbulence in the inertial subrange, the reflectivity of the clear air may be expressed as \ud835\udf02_a = 0.38 C_n^2 \ud835\udf06^-1/3, where \ud835\udf06 is the radar wavelength and C_n^2 is the structure parameter that characterizes the strength of the refractive index fluctuations (Tatarski 1961)."}]}, {"title": "Irrigation", "paragraphs": [{"qas": [{"is_impossible": false, "question": "Where were observations collected?", "id": "160", "answers": [{"text": "southeast Nebraska", "answer_start": 86}]}, {"is_impossible": false, "question": "What longitude is irrigation dominant west of?", "id": "161", "answers": [{"text": "96.9\u00b0W", "answer_start": 761}]}, {"is_impossible": false, "question": "When were the intensive operation periods conducted?", "id": "162", "answers": [{"text": "29th May-16th June 2018 (IOP 1) and July 17th-30th, 2018 (IOP 2)", "answer_start": 275}]}, {"is_impossible": true, "question": "How are slope circulations modified by irrigation?", "id": "163", "answers": []}, {"is_impossible": true, "question": "What is the nearest city to GRAINEX?", "id": "164", "answers": [], "plausible_answers": [{"text": "Nebraska", "answer_start": 96}]}], "context": "Observations collected during GRAINEX, conducted during the growing season of 2018 in southeast Nebraska (Figure 1), are used to isolate the slope circulations and investigate how they are modified by irrigation. GRAINEX consisted of two Intensive Operation Periods (IOPs): 29th May-16th June 2018 (IOP 1) and July 17th-30th, 2018 (IOP 2) with reduced observations between those periods (Rappin et al., 2021). IOP 1 corresponds to the early growing period, when irrigation is limited, and IOP 2 occurs during the mid-growing season, which is characterized by vigorous crop growth and substantial irrigation. The GRAINEX domain (\u223c100 \u00d7 100 km) straddles the boundary between irrigated and non-irrigated croplands with irrigation being dominant west of longitude 96.9\u00b0W (Figure S1 in Supporting Information S1; Xie et al., 2021)."}]}, {"title": "Soil Moisture", "paragraphs": [{"qas": [{"is_impossible": false, "question": "Why is soil moisture important?", "id": "165", "answers": [{"text": "Soil moisture is one of the smallest components of the hydrologic cycle, yet it plays an important role as a critical land surface parameter influencing Earth's water, energy, and carbon cycles", "answer_start": 0}]}, {"is_impossible": false, "question": "How can soil mositure be measured?", "id": "166", "answers": [{"text": "Soil moisture can be estimated by several methods, including in situ monitoring, remote sensing, and numerical modeling.", "answer_start": 510}]}, {"is_impossible": false, "question": "Which method is currently considered the best for measuring soil moisture?", "id": "167", "answers": [{"text": "While each is valuable, no one method for obtaining soil moisture information is perfect, as each has unique limitations relative to attributes such as accuracy, historical record, data availability, spatial distribution and latency. ", "answer_start": 631}]}, {"is_impossible": true, "question": "What units of measurement are used to describe soil moisture?", "id": "168", "answers": []}, {"is_impossible": true, "question": "Can soil moisture help forecast potential drought conditions?", "id": "169", "answers": []}], "context": "Soil moisture is one of the smallest components of the hydrologic cycle, yet it plays an important role as a critical land surface parameter influencing Earth's water, energy, and carbon cycles (Figure 1). As a result, natural resources and the economic activities that depend on them are directly impacted by soil moisture levels in unique ways that may not be fully captured by more traditional meteorological and hydrologic indicators such as precipitation, temperature, evapotranspiration, and streamflow. Soil moisture can be estimated by several methods, including in situ monitoring, remote sensing, and numerical modeling. While each is valuable, no one method for obtaining soil moisture information is perfect, as each has unique limitations relative to attributes such as accuracy, historical record, data availability, spatial distribution and latency. Yet, when used in complementary ways, these three methods of estimation have the potential to provide a comprehensive picture of soil moisture levels to support a wide range of applications."}]}, {"title": "Aerosol", "paragraphs": [{"qas": [{"is_impossible": false, "question": "How was the aerosol sampled?", "id": "170", "answers": [{"text": "through 3/800 copper tubing running from the instrument laboratory to the outside through a port in the window \u223c20 m a.g.l.", "answer_start": 386}]}, {"is_impossible": false, "question": "Where was the aerosol data collected?", "id": "171", "answers": [{"text": "the University of Manchester", "answer_start": 32}]}, {"is_impossible": false, "question": "Which type of aerosol was expected to be sampled?", "id": "172", "answers": [{"text": "a mixture of BC from local as well as regional sources", "answer_start": 736}]}, {"is_impossible": true, "question": "What effect does an urban area have on whether black carbon is hydrophilic or hydrophobic?", "id": "173", "answers": []}, {"is_impossible": true, "question": "Which local and regional sources of black carbon were studied?", "id": "174", "answers": []}], "context": "\"Ambient data were collected at the University of Manchester between 3 and 16 August 2010. Manchester is located at the center of the British Isles and prevailing winds are southerly/westerly resulting in a maritime climate. Manchester is situated on the urban east-west corridor that connects Leeds and Liverpool, so incoming air may have already acquired some BC. Aerosol was sampled through 3/800 copper tubing running from the instrument laboratory to the outside through a port in the window \u223c20 m a.g.l. The laboratory is located \u223c100 m from a major urban corridor (with a scheduled passenger bus frequency of one per minute during daytime) and around 2 km south of the Manchester city center. We therefore expect to have sampled a mixture of BC from local as well as regional sources.\""}]}, {"title": "Local Climate Zones", "paragraphs": [{"qas": [{"is_impossible": false, "question": "What is the scale of the classes called \"local climate zones\"?", "id": "175", "answers": [{"text": "local", "answer_start": 93}]}, {"is_impossible": false, "question": "How long do the screen-height temperature regimes of an LCZ persist?", "id": "176", "answers": [{"text": "year-round", "answer_start": 640}]}, {"is_impossible": false, "question": "Where and when are the screen-height temperature regimes most apparent?", "id": "177", "answers": [{"text": "over dry surfaces, on calm, clear nights, and in areas of simple relief", "answer_start": 533}]}, {"is_impossible": true, "question": "What is logical division?", "id": "178", "answers": []}, {"is_impossible": true, "question": "What are the names of the local climate zones", "id": "179", "answers": [], "plausible_answers": [{"text": "cities (e.g., parks, commercial cores), natural biomes (e.g., forests, deserts), and agricultural lands (e.g., orchards, cropped fields)", "answer_start": 721}]}], "context": "Hereafter, all classes to emerge from logical division of the landscape universe are called \"local climate zones\" (LCZs; Table 2) (Stewart 2011a). The name is appropriate because the classes are local in scale, climatic in nature, and zonal in representation. We formally define local climate zones as regions of uniform surface cover, structure, material, and human activity that span hundreds of meters to several kilometers in horizontal scale. Each LCZ has a characteristic screen-height temperature regime that is most apparent over dry surfaces, on calm, clear nights, and in areas of simple relief. These temperature regimes persist year-round and are associated with the homogeneous environments or ecosystems of cities (e.g., parks, commercial cores), natural biomes (e.g., forests, deserts), and agricultural lands (e.g., orchards, cropped fields). Each LCZ is individually named and ordered by one (or more) distinguishing surface property, which in most cases is the height/packing of roughness objects or the dominant land cover. The physical properties of all zones are measurable and nonspecific as to place or time (Tables 3 and 4)."}]}, {"title": "Clouds", "paragraphs": [{"qas": [{"is_impossible": false, "question": "Where is the Earth covered by fair-weather cumulus clouds?", "id": "180", "answers": [{"text": "large areas of the tropical and subtropical oceans in the trade-wind regions", "answer_start": 38}]}, {"is_impossible": false, "question": "Which key boundary-layer processes are parameterized in climate models?", "id": "181", "answers": [{"text": "convection and turbulence", "answer_start": 563}]}, {"is_impossible": false, "question": "Why is there a large dispersion in model-based estimates of cloud feedback?", "id": "182", "answers": [{"text": "climate models predict different low-level cloud changes in response to warming", "answer_start": 200}]}, {"is_impossible": true, "question": "What is the average height of fair-weather cumulus clouds?", "id": "183", "answers": []}, {"is_impossible": true, "question": "What atmospheric phenomenon is largely responsible for driving the trade-winds?", "id": "184", "answers": []}], "context": "Fair-weather cumulus clouds, covering large areas of the tropical and subtropical oceans in the trade-wind regions, play a central role in the tropical cloud feedback uncertainties in climate models. Climate models predict different low-level cloud changes in response to warming, which results in a large dispersion in model-based estimates of cloud feedback and climate sensitivity. This large dispersion in model responses arises from differences in the balance of the key boundary-layer physical processes that are parameterized in climate models, especially convection and turbulence. Given the importance of low-level cloud feedbacks in climate change projections, understanding the factors controlling the low-level cloudiness across a wide range of temporal and spatial scales in a hierarchy of numerical models and in observations has emerged as an active research area."}]}, {"title": "Atmospheric Chemistry", "paragraphs": [{"qas": [{"is_impossible": false, "question": "How is tropospheric ozone formed?", "id": "185", "answers": [{"text": "Ozone (O3) is formed when hydrocarbons are oxidized in the presence of nitrogen oxides (NOx = NO + NO2) and sunlight", "answer_start": 0}]}, {"is_impossible": false, "question": "What trace gases are emitted by wildfires?", "id": "186", "answers": [{"text": "Along with carbon monoxide (CO), methane (CH4), and carbon dioxide (CO2), hundreds of different non-methane volatile organic compounds (NMVOCs) with lifetimes ranging from minutes to months (Atkinson and Arey, 2003) are emitted during biomass burning", "answer_start": 219}]}, {"is_impossible": false, "question": "What is the major source of OH reactivity within smoke plumes?", "id": "187", "answers": [{"text": "VOCs", "answer_start": 357}]}, {"is_impossible": true, "question": "How is OH formed in the atmosphere?", "id": "188", "answers": []}, {"is_impossible": true, "question": "How much does biomass burning contribute to NOx pollution?", "id": "189", "answers": []}], "context": "Ozone (O3) is formed when hydrocarbons are oxidized in the presence of nitrogen oxides (NOx = NO + NO2) and sunlight (Sillman, 1999). Wildfires emit many trace gas species that contribute to tropospheric O3 production. Along with carbon monoxide (CO), methane (CH4), and carbon dioxide (CO2), hundreds of different non-methane volatile organic compounds (NMVOCs) with lifetimes ranging from minutes to months (Atkinson and Arey, 2003) are emitted during biomass burning (Akagi et al., 2011; Gilman et al., 2015). Due to relatively large emissions of CO2, CO, CH4, and NOx, the contribution of VOCs to the total emissions from fires on a molar basis is small (< 1 %). However, VOCs dominate the OH reactivity in smoke plumes (Gilman et al., 2015). Recent observations of the evolution of VOCs within aging smoke plumes indicate that OH can be elevated in young biomass burning plumes (Hobbs et al., 2003; Yokelson et al., 2009; Akagi et al., 2012; Liu et al., 2016) in part due to the photolysis of oxygenated VOCs (Mason et al., 2001), which make a large contribution to the total emitted VOC mass (Stockwell et al., 2015). Elevated OH may reduce the lifetime of emitted VOCs and increase oxidation rates and potential O3 production. "}]}, {"title": "Pollution", "paragraphs": [{"qas": [{"is_impossible": false, "question": "How will scientists be connected?", "id": "190", "answers": [{"text": "A network across different scientific communities.", "answer_start": 0}]}, {"is_impossible": false, "question": "Where is there a need to advance understanding of air pollution-terrestrial ecosystems?", "id": "191", "answers": [{"text": "regions historically underrepresented in atmospheric and ecological observational datasets", "answer_start": 214}]}, {"is_impossible": false, "question": "What regions are underrepresented?", "id": "192", "answers": [{"text": "Africa, South America, and Oceania.", "answer_start": 474}]}, {"is_impossible": true, "question": "Why is this experiment so costly?", "id": "193", "answers": []}, {"is_impossible": true, "question": "Why is there a need to advance understanding of air pollution?", "id": "194", "answers": []}], "context": "A network across different scientific communities will also facilitate connections among scientists around the world. There is a need to advance understanding of air pollution-terrestrial ecosystem interactions in regions historically underrepresented in atmospheric and ecological observational datasets. Here \"underrepresented regions\" are places with potentially unique air pollution-terrestrial ecosystem interactions but without any or sufficient observations, such as Africa, South America, and Oceania. While local scientists make observations in underrepresented regions, funding opportunities are not always accessible or sufficient to cover the costs (e.g., labor, instrumentation, data stor-age, computational time, publication and travel) necessary to publicly distribute datasets and disseminate findings."}]}]} |